db = a
elif o == "-f":
filename = a
else:
usage()
if filename is None:
usage()
count = 0
buf = []
progressbar = ProgressBar(widgets = [ AnimatedMarker()
, ' '
, Timer()
, ', # of Tweets: '
, Counter()
],
maxval = UnknownLength)
progressbar.start()
ts = TweetStore(db)
with open(filename) as f:
for line in islice(f, 1, None, 2):
buf.append(json.loads(line))
if len(buf) > CHUNK_SIZE:
ts.put(buf)
del buf[:]
count += 1
progressbar.update(count)
classifier = "classifier.pickle"
opts, args = getopt.getopt(sys.argv[1:], "hc:d:k:s:e:")
for o, a in opts:
if o == "-d":
db = a
elif o == "-c":
classifier = a
elif o == "-k":
keywords.append(a)
elif o == "-s":
start = datetime.strptime(a, "%Y-%M-%d")
elif o == "-e":
end = datetime.strptime(a, "%Y-%M-%d")
else:
usage()
sys.exit(0)
classifier = Classifier.load(classifier)
aggregator = RetweetWeightedAggregator()
ts = TweetStore(db)
for t in ts.get(keywords, start, end):
s = classifier.classify(t)
print("%s -- sentiment: %s" % (tweet.to_ascii(t)[tweet.TEXT], "positive" if (s == 1) else "negative"))
aggregator.add(t, s)
print("Aggregated sentiment: %f" % aggregator.get_sentiment())
print("ID of last tweet: %d" % aggregator.get_last_id())
print("Total number of tweets: %d" % aggregator.get_num())
#
# Jun Jen CHAN (341759)
# Daniel TEH (558424)
# Tou LEE (656128)
# David MONROY (610346)
# Jaime MARTINEZ (642231)
import json, csv, sys
from tweetstore import TweetStore
# Python script for importing tweets from text file;
# Usage: importTweets.py *sourcefile *couchdbname
# Daniel Teh
filename = sys.argv[1]
storage = TweetStore(sys.argv[2])
i = 0
with open(filename, 'rb') as tweetfile:
reader = csv.DictReader(tweetfile)
for tweet in reader:
decoded = json.loads(tweet['value'])
try:
storage.save_tweet(decoded)
except:
print("Tweet %d already exists.. skipping" % i)
print("Importing tweet no. %d" % i)
i+=1
print ("Inserted %d tweets" % i)
## Tweet Harvester - Search API
##
## The twitter search api generally only allows for searches up to 1 week into the
## past when scraping for tweets.
## The decision to only use a single node for the Search API was because the city
## of Adelaide does not get enough volume to warrent several harvesters at once.
## The decision not to delve into single users timelines stems from the desire
## to keep data as unbiased.
##
## Daniel Teh
import tweepy, json
from tweetstore import TweetStore
import time
import datetime
storage = TweetStore('tweets_adelaide')
@classmethod
def parse(cls, api, raw):
status = cls.first_parse(api, raw)
setattr(status, 'json', json.dumps(raw))
return status
tweepy.models.Status.first_parse = tweepy.models.Status.parse
tweepy.models.Status.parse = parse
## OAuth Keys
# Application Key
consumer_key = "kuPrFsWufTx87nCSc4HKJ6HVU"